{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial 8b - Tolerancing, Monte Carlo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "nbsphinx-toctree"
    ]
   },
   "source": [
    "### September 2024"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this tutorial, we will continue to explore the tolerancing capabilities of Optiland and will introduce Monte Carlo analysis. Monte Carlo analysis involves simulating a large number of random variations of an optical system, which helps to understand the statistical distribution of potential performance outcomes for a system. It is particularly valuable for understanding the impact of manufacturing defects and environmental conditions.\n",
    "\n",
    "The Monte Carlo analysis in Optiland is fundamentally similar to the sensitivity analysis, which was introduced in tutorial 8a. We require the following components to perform a Monte Carlo analysis:\n",
    "\n",
    "1. Optic - the optical system to be analyzed.\n",
    "2. Operands - the metrics which are assessed e.g., wavefront error.\n",
    "3. Perturbations - the variations applied to the optic or a surface of an optic e.g., surface tilt.\n",
    "4. Compensators - a parameter of the optical system that can be adjusted to counteract the effects of a perturbation.\n",
    "\n",
    "In this example, we will perform a Monte Carlo analysis on a Cooke triplet to understand how common variations, such as surface decenter and tilt, can impact the optical performance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from optiland.samples.objectives import CookeTriplet\n",
    "from optiland.tolerancing.core import Tolerancing\n",
    "from optiland.tolerancing.monte_carlo import MonteCarlo\n",
    "from optiland.tolerancing.perturbation import DistributionSampler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Defining the tolerancing object\n",
    "\n",
    "The first step is to define our optic and pass it to a Tolerancing object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "optic = CookeTriplet()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "tolerancing = Tolerancing(optic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Adding perturbations\n",
    "\n",
    "The Monte Carlo anlaysis requires that we apply random perturbations to optical properties of our system. We will apply both random tilt and random decenter to every surface of the triplet, so 6 surfaces in total."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will apply perturbations to every surface and in both the x and y axes.\n",
    "\n",
    "Properties for tilt perturbation:\n",
    "\n",
    "- Normal distribution, mean = 0, standard deviation = 0.01 radians\n",
    "\n",
    "Properties for decenter perturbation:\n",
    "\n",
    "- Normal distribution, mean = 0, standard deviation = 0.1 mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through all surfaces and add perturbations\n",
    "for k in range(1, 7):\n",
    "    # X-tilt\n",
    "    sampler = DistributionSampler(\"normal\", loc=0, scale=0.01)\n",
    "    tolerancing.add_perturbation(\"tilt\", sampler, surface_number=k, axis=\"x\")\n",
    "\n",
    "    # Y-tilt\n",
    "    sampler = DistributionSampler(\"normal\", loc=0, scale=0.01)\n",
    "    tolerancing.add_perturbation(\"tilt\", sampler, surface_number=k, axis=\"y\")\n",
    "\n",
    "    # X-decenter\n",
    "    sampler = DistributionSampler(\"normal\", loc=0, scale=0.1)\n",
    "    tolerancing.add_perturbation(\"decenter\", sampler, surface_number=k, axis=\"x\")\n",
    "\n",
    "    # Y-decenter\n",
    "    sampler = DistributionSampler(\"normal\", loc=0, scale=0.1)\n",
    "    tolerancing.add_perturbation(\"decenter\", sampler, surface_number=k, axis=\"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Adding operands\n",
    "\n",
    "\n",
    "We wish to monitor the impact of perturbations on our triplet. We choose to monitor the following metrics:\n",
    "\n",
    "- RMS spot size for (Hx, Hy) = (0, 1) field\n",
    "- mean OPD difference for (Hx, Hy) = (0, 1) field\n",
    "- real y-intercept on image plane for (Hx, Hy) = (0, 1) field\n",
    "\n",
    "The syntax used here follows that used in the optimization module when variables are defined. In general, we pass the following arguments to the \"add_operand\" method to create a new operand:\n",
    "\n",
    "- operand type - see optiland.optimization.operand for complete list of options.\n",
    "- input_data - a dictionary containing the optic instance at a minimum, and generally other parameters related to the operand, such as wavelength.\n",
    "- target (optional) - if an operand has a target, we may specify it here. This is only used when we apply compensation, or optimize the system to counteract perturbations.\n",
    "- weight (optional) - if an operand is more important than others, it may be given a larger weight during compensation.\n",
    "\n",
    "We define the 3 operands as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_data = {\n",
    "    \"optic\": optic,\n",
    "    \"surface_number\": -1,\n",
    "    \"Hx\": 0,\n",
    "    \"Hy\": 1,\n",
    "    \"wavelength\": 0.55,\n",
    "    \"num_rays\": 5,\n",
    "}\n",
    "tolerancing.add_operand(\"rms_spot_size\", input_data, target=0)\n",
    "\n",
    "input_data = {\"optic\": optic, \"Hx\": 0, \"Hy\": 1, \"wavelength\": 0.55, \"num_rays\": 5}\n",
    "tolerancing.add_operand(\"OPD_difference\", input_data)\n",
    "\n",
    "input_data = {\n",
    "    \"optic\": optic,\n",
    "    \"surface_number\": -1,\n",
    "    \"Hx\": 0,\n",
    "    \"Hy\": 1,\n",
    "    \"Px\": 0,\n",
    "    \"Py\": 0,\n",
    "    \"wavelength\": 0.55,\n",
    "}\n",
    "tolerancing.add_operand(\"real_y_intercept\", input_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Run Monte Carlo analysis\n",
    "\n",
    "\n",
    "We are now ready to run our Monte Carlo analysis. We first define our Monte Carlo analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "monte_carlo = MonteCarlo(tolerancing)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then run our Monte Carlo analysis. We choose to run 1000 iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "monte_carlo.run(num_iterations=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. View and analyze results\n",
    "\n",
    "\n",
    "There are several ways to view the output data of a Monte Carlo analysis:\n",
    "\n",
    "- Plot the distributions of the performance metrics\n",
    "- Plot the cumulative distribution function (CDF) of the metrics\n",
    "- Plot a heatmap showing the correlations between the perturbations and the metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monte_carlo.view_histogram(kde=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monte_carlo.view_cdf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monte_carlo.view_heatmap(vmin=-0.2, vmax=0.2, figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The heatmap gives an indication of the correlation between the metrics and the various pertrurbations applied. The strongest correlations exist between the real y-intercept and several of the surface tilts and decenters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As with the sensitivity analysis, we can also retrieve the Monte Carlo results for further analysis:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = monte_carlo.get_results()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tilt X, Surface 1</th>\n",
       "      <th>Tilt Y, Surface 1</th>\n",
       "      <th>Decenter X, Surface 1</th>\n",
       "      <th>Decenter Y, Surface 1</th>\n",
       "      <th>Tilt X, Surface 2</th>\n",
       "      <th>Tilt Y, Surface 2</th>\n",
       "      <th>Decenter X, Surface 2</th>\n",
       "      <th>Decenter Y, Surface 2</th>\n",
       "      <th>Tilt X, Surface 3</th>\n",
       "      <th>Tilt Y, Surface 3</th>\n",
       "      <th>...</th>\n",
       "      <th>Tilt Y, Surface 5</th>\n",
       "      <th>Decenter X, Surface 5</th>\n",
       "      <th>Decenter Y, Surface 5</th>\n",
       "      <th>Tilt X, Surface 6</th>\n",
       "      <th>Tilt Y, Surface 6</th>\n",
       "      <th>Decenter X, Surface 6</th>\n",
       "      <th>Decenter Y, Surface 6</th>\n",
       "      <th>0: rms spot size</th>\n",
       "      <th>1: OPD difference</th>\n",
       "      <th>2: real y intercept</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.006221</td>\n",
       "      <td>-0.008661</td>\n",
       "      <td>-0.061028</td>\n",
       "      <td>-0.025816</td>\n",
       "      <td>0.016382</td>\n",
       "      <td>-0.007767</td>\n",
       "      <td>0.123581</td>\n",
       "      <td>0.138610</td>\n",
       "      <td>0.002398</td>\n",
       "      <td>0.002283</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000548</td>\n",
       "      <td>0.237340</td>\n",
       "      <td>0.033150</td>\n",
       "      <td>-0.001259</td>\n",
       "      <td>0.011874</td>\n",
       "      <td>0.122432</td>\n",
       "      <td>-0.079730</td>\n",
       "      <td>0.083058</td>\n",
       "      <td>0.152733</td>\n",
       "      <td>19.558908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.001218</td>\n",
       "      <td>-0.000293</td>\n",
       "      <td>-0.024775</td>\n",
       "      <td>-0.035325</td>\n",
       "      <td>-0.001651</td>\n",
       "      <td>-0.014804</td>\n",
       "      <td>-0.002968</td>\n",
       "      <td>0.039857</td>\n",
       "      <td>-0.008041</td>\n",
       "      <td>-0.004399</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010716</td>\n",
       "      <td>-0.056133</td>\n",
       "      <td>0.024629</td>\n",
       "      <td>-0.009219</td>\n",
       "      <td>-0.016362</td>\n",
       "      <td>-0.041900</td>\n",
       "      <td>-0.185342</td>\n",
       "      <td>0.069057</td>\n",
       "      <td>0.503264</td>\n",
       "      <td>17.628797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000197</td>\n",
       "      <td>-0.007129</td>\n",
       "      <td>0.049039</td>\n",
       "      <td>0.028964</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>-0.004770</td>\n",
       "      <td>-0.129937</td>\n",
       "      <td>-0.172918</td>\n",
       "      <td>-0.005845</td>\n",
       "      <td>0.004061</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002730</td>\n",
       "      <td>-0.021001</td>\n",
       "      <td>0.089267</td>\n",
       "      <td>0.009255</td>\n",
       "      <td>-0.025322</td>\n",
       "      <td>0.229231</td>\n",
       "      <td>-0.112551</td>\n",
       "      <td>0.156009</td>\n",
       "      <td>0.591829</td>\n",
       "      <td>18.787886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.004874</td>\n",
       "      <td>0.000841</td>\n",
       "      <td>0.015796</td>\n",
       "      <td>0.016955</td>\n",
       "      <td>-0.009637</td>\n",
       "      <td>0.003914</td>\n",
       "      <td>-0.044681</td>\n",
       "      <td>-0.041809</td>\n",
       "      <td>0.008580</td>\n",
       "      <td>-0.003123</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003756</td>\n",
       "      <td>0.208429</td>\n",
       "      <td>-0.057769</td>\n",
       "      <td>0.004500</td>\n",
       "      <td>-0.011888</td>\n",
       "      <td>0.004488</td>\n",
       "      <td>-0.105027</td>\n",
       "      <td>0.060417</td>\n",
       "      <td>0.480440</td>\n",
       "      <td>17.122025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.022222</td>\n",
       "      <td>0.008179</td>\n",
       "      <td>-0.019002</td>\n",
       "      <td>-0.009676</td>\n",
       "      <td>-0.001012</td>\n",
       "      <td>-0.010193</td>\n",
       "      <td>0.103021</td>\n",
       "      <td>-0.050787</td>\n",
       "      <td>0.018299</td>\n",
       "      <td>0.007881</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009875</td>\n",
       "      <td>-0.133196</td>\n",
       "      <td>-0.038400</td>\n",
       "      <td>-0.004322</td>\n",
       "      <td>-0.010546</td>\n",
       "      <td>0.076583</td>\n",
       "      <td>0.195792</td>\n",
       "      <td>0.091870</td>\n",
       "      <td>0.835800</td>\n",
       "      <td>16.705053</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Tilt X, Surface 1  Tilt Y, Surface 1  Decenter X, Surface 1  \\\n",
       "0          -0.006221          -0.008661              -0.061028   \n",
       "1          -0.001218          -0.000293              -0.024775   \n",
       "2           0.000197          -0.007129               0.049039   \n",
       "3           0.004874           0.000841               0.015796   \n",
       "4           0.022222           0.008179              -0.019002   \n",
       "\n",
       "   Decenter Y, Surface 1  Tilt X, Surface 2  Tilt Y, Surface 2  \\\n",
       "0              -0.025816           0.016382          -0.007767   \n",
       "1              -0.035325          -0.001651          -0.014804   \n",
       "2               0.028964           0.001362          -0.004770   \n",
       "3               0.016955          -0.009637           0.003914   \n",
       "4              -0.009676          -0.001012          -0.010193   \n",
       "\n",
       "   Decenter X, Surface 2  Decenter Y, Surface 2  Tilt X, Surface 3  \\\n",
       "0               0.123581               0.138610           0.002398   \n",
       "1              -0.002968               0.039857          -0.008041   \n",
       "2              -0.129937              -0.172918          -0.005845   \n",
       "3              -0.044681              -0.041809           0.008580   \n",
       "4               0.103021              -0.050787           0.018299   \n",
       "\n",
       "   Tilt Y, Surface 3  ...  Tilt Y, Surface 5  Decenter X, Surface 5  \\\n",
       "0           0.002283  ...           0.000548               0.237340   \n",
       "1          -0.004399  ...           0.010716              -0.056133   \n",
       "2           0.004061  ...          -0.002730              -0.021001   \n",
       "3          -0.003123  ...          -0.003756               0.208429   \n",
       "4           0.007881  ...          -0.009875              -0.133196   \n",
       "\n",
       "   Decenter Y, Surface 5  Tilt X, Surface 6  Tilt Y, Surface 6  \\\n",
       "0               0.033150          -0.001259           0.011874   \n",
       "1               0.024629          -0.009219          -0.016362   \n",
       "2               0.089267           0.009255          -0.025322   \n",
       "3              -0.057769           0.004500          -0.011888   \n",
       "4              -0.038400          -0.004322          -0.010546   \n",
       "\n",
       "   Decenter X, Surface 6  Decenter Y, Surface 6  0: rms spot size  \\\n",
       "0               0.122432              -0.079730          0.083058   \n",
       "1              -0.041900              -0.185342          0.069057   \n",
       "2               0.229231              -0.112551          0.156009   \n",
       "3               0.004488              -0.105027          0.060417   \n",
       "4               0.076583               0.195792          0.091870   \n",
       "\n",
       "   1: OPD difference  2: real y intercept  \n",
       "0           0.152733            19.558908  \n",
       "1           0.503264            17.628797  \n",
       "2           0.591829            18.787886  \n",
       "3           0.480440            17.122025  \n",
       "4           0.835800            16.705053  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conclusions\n",
    "\n",
    "- This tutorial demonstrated Monte Carlo analyses in Optiland.\n",
    "- Monte Carlo analysis is a statistical technique to explore possible system performance variations due to manufacturing tolerances or environmental conditions.\n",
    "- Several plotting functions are available via the Monte Carlo analysis object, including plotting of distributions, CDFs, and heatmaps."
   ]
  }
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